Early detection of a traffic accident not only enhances a success rate in life saving by fast rescue operation, but also alleviates accident-related traffic congestion by speedup of the police inspection at the site. Therefore, various types of automation in recognition of traffic accident are expected. In order to achieve a high recognition rate of traffic accidents, it is necessary to correctly track moving objects by processing pictures captured by a camera.
FIG. 28 schematically illustrates pictures at times t=1 to 4 captured by a camera disposed above a halfway line of an expressway.
Since vehicles frequently overlap with each other in the captured pictures, it is difficult to track each vehicle by image processing. To overcome this problem, there is a need to dispose a plurality of cameras along the road and then to synthetically process all pictures captured by the cameras.
However, the necessity to install a plurality of cameras and image processors increases costs. In addition, the necessity to associate and synthetically process pictures captured by the cameras makes the processing complicated.
To overcome these problems, the present inventors have disclosed a method of tracking moving objects in pictures backward in time in the following manner (Japanese Patent Application Publication No. 2002-133421).
Time-series pictures at times t=1 to 4 are temporarily stored. Starting from time t=4, vehicles M1 and M2 are identified, and motion vectors of the vehicles M1 and M2 are determined. Images of the vehicles M1 and M2 in the picture at time t=4 are moved with the determined motion vectors to estimate a corresponding picture at t=3 in which the vehicles M1 and M2 are identified. Based on the correlation between the estimated picture and the actual picture at t=3, the vehicles M1 and M2 are identified in the picture at t=3.
Next, the same process is performed for the pictures at t=3 and t=2, so that the vehicles M1 and M2 are identified in the picture at t=2. Then, the same process is performed for the pictures at t=2 and t=1, so that the vehicles M1 and M2 are identified in the picture at t=1.
This method makes it possible to track vehicles M1 and M2 using a single camera.
However, in actuality, since pictures are processed at a rate of, for example, 12 frames/sec, there are disadvantages in that a large storage capacity is required for the time-series pictures, and the processing time is also increased.
In addition, if the size of each image block is reduced to improve the accuracy of recognition of the boundary of moving object, there arises a problem that it is difficult to determine motion vectors with block matching.
In the above Japanese Patent Application Publication No. 2002-133421, each captured picture is divided into blocks, each of which has a size of, for example, 8×8 pixels, and the image of each block of a captured picture and the image of a corresponding block of a separate background picture are compared to determine whether or not an moving object is present in the block.
The background picture must be updated since it varies with time. Regarding all the pictures captured for the past 10 minutes, for example, a histogram of the pixel values of a corresponding pixel position is made for each pixel position, and a picture, each pixel value of which is equal to the most frequent pixel value (i.e., mode) of the corresponding histogram, is defined as a background picture.